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Abstract

As primary pollinators in agricultural settings, managed honey bee colonies (Apis mellifera L.) are a highly value commodity for which demand is only growing. With high levels of colony loss experienced in the USA and around the world, there is demand for a better understanding of the drivers of colony mortality and identification of suites of management practices which are optimal for colony survivorship. This dissertation responds to these demands by summarizing the state of knowledge on the causes of colony loss (Chapter 1); describing the epidemiological tools used to investigate honey bee colony health (Chapter 2); describing the variability of colony loss across stakeholder typology, regions, seasons and years (Chapters 3 and 4); and investigating the association between management practices and colony mortality (Chapter 5).
Honey bee health, and ultimately, colony loss, is affected by multiple stressors acting concomitantly and sometimes interacting. Those stressors include pests and diseases, forage availability and pesticide exposure. Management practices have the potential, when used judiciously, to alleviate some of those stressors. Investigations of sets of management practices have been frustrated by the lack of methodology to handle large complex and incomplete datasets that are typical in observational studies. Using long term observational data obtained from the Bee Informed Partnership monitoring of honey bee colony losses and management practices in the US, we were able to describe the variation in colony loss across years, seasons, States and stakeholder’s types. In parallel, we summarized management information into a quality index, based on experts’ opinion, and confirmed the association between management practices quality and overwintering colony loss. Further, we ranked individual practices based on their associated potential reduction in colony mortality. Because our method accounts for the pre-existing prevalence of practices, we propose that those sets of practices should be prioritized as recommendations, rather than those identified by experts, to derive the highest reduction in risk of colony mortality. The methodology we developed could benefit other Ag or epidemiological systems interested in the summarization of a great number of practices and their prioritization based on highest potential to reduce risk.